Description

Key Responsibilities

AI Development

Design and implement generative AI features leveraging models like GPT-5, Llama, or other foundational models Fine-tune and optimize AI models for specific use cases and domains (optional, good to have) Create prompt engineering frameworks and templates to ensure consistent AI behavior Develop retrieval-augmented generation (RAG) systems that combine vector databases with LLMs Working knowledge of LLM evaluation and observability platforms

Frontend Development (Basic Exposure)

Build responsive, accessible web interfaces for AI-powered applications using modern frameworks (React, Vue, Angular, MUI) Design intuitive UIs that make complex AI capabilities understandable and usable Implement real-time features for AI interactions (streaming responses, progressive rendering) Develop visualization components for AI outputs and confidence metrics Backend Development

Create robust APIs on python and similar framework and services to interface with AI models and external services Design scalable architectures that can handle high-throughput AI inference Implement efficient data processing pipelines for AI training and inference Integrate with vector databases, document stores, and other AI-specific infrastructure DevOps & MLOps

Set up CI/CD pipelines for AI application deployment Implement monitoring, logging, and alerting for AI systems Optimize infrastructure for cost-effective AI deployment Required Skills & Experience

Technical Skills

3+ years of full-stack development experience (JavaScript/TypeScript,

3+ Python(must))

1+ years working with AI/ML technologies, particularly generative AI

Experience with at least one major LLM framework (LangChain, Langgraph) Proficiency with vector databases (Pinecone, Mongo, FAISS, etc.) Strong understanding of REST APIs, GraphQL, and microservices architecture (Optional, Good to have) Experience with Git, Github actions, cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes) AI-Specific Knowledge

Deep understanding of LLMs, including their capabilities and limitations Experience with prompt engineering and RAG architecture Knowledge of embedding models and vector similarity search Understanding of AI evaluation metrics and testing methodologies Preferred Qualifications

Experience developing commercial AI applications or products Knowledge of AI safety practices and responsible AI deployment Background in NLP, computer vision, or other AI specialties Experience with streaming architectures for real-time AI applications Education

Bachelor's degree or higher in Computer Science, Software Engineering, AI/ML, or related field Relevant certifications in cloud platforms, AI frameworks, or software development Personal Attributes

Strong problem-solving skills with a creative approach to AI challenges Excellent communication skills to explain complex AI concepts to stakeholders Ability to stay current with rapidly evolving AI technologies and best practices Self-motivated with the ability to work independently and in cross-functional teams Keen interest in the ethical implications of AI technology

Key Skills

Education

Bachelor’s degree